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EXPERT SYSTEM

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16.1 RULE-BASED EXPLANATION

It has been recognized that automatic explanation requires access to a domain model .

In other words , as a program needs a modicum of domain knowledge in order to acquire more knowledge , so a program need access to a representation of deep knowledge about the domain in order to explain its own behavior .

Such knowledge is essential to bridge the gap between the-lower level implementation and the higher-level strategy that the system was pursuing .

16.1 RULE-BASED EXPLANATION(CONT.)

There is indeed an intimate connection between the problems of knowledge elicitation and explanation , in that the way that knowledge is acquired and compiled has effect upon the way in which it can subsequently be used to explain system output .

16.1.1 MYCIN’s EXPLANATION system :

The explanation module of MYCIN system was automatically invoked at the end of every consultation .

To explain how the value of a particular medical parameters was established , the module retrieved the list of rules that were successfully applied and printed them , along with the conclusions drawn .

It also allowed the user to interrogate the system about the consultation , and ask more general questions.

All question-answering facilities were based upon the system’s ability to :

1. Display the rule .

2. Record rule invocations

3. Use rule indexing .

16.1.1 MYCIN’s EXPLANATION system:(CONT.)

A consultation with a backward chaining expert system involves a search through a tree of goals .

Consequently, inquiries during a consultation fall into two types :

1. Those that ask WHY a particular question was put .

2. Those that ask HOW a particular conclusion was reached .

To Answer a WHY Questions , one must look up the tree to see what the higher goals the system is trying to achieve .

To answer a HOW question , one must look down the tree to see what subgoals were satisfied to achieve the goal.

Note that the explanation process can be considered as kind of tree traversal .

16.1.1 MYCIN’s EXPLANATION system:(CONT.)

IF:1) The stain of the organism is gramneg, and

2) The Morphology of the organism is rod,and

3) the aerobicity of the organism is aerobic

THEN:There is strongly suggestive evidence(0.8)

that the class of the organism is entrobacteriaceae .

ENTROBACTERIACEAE

WHY??

HOW??

STAIN

MORPHOLOGY

AEROBICITY

16.1.1 MYCIN’s EXPLANATION system:(CONT.)

It can simply cite the production rule which states that gram negative staining, in conjunction with various other conditions, would suggest that the class of the organism was entrobacteriaceae , and that the current goal was to identify the organism.

MYCIN also maintain a record of the decision it makes , and uses this record to explain and justify its decision in response to HOW questions .

In reply, MYCIN cites the rules that it applied , its degree of certainty in that decision , and the last question asked . General questions can also be asked , these reference the rules without considering the state of the dynamic database with respect to a particular patient.

For example : What do you prescribe for pseudomonas infection?

16.1.2 EXPLANATION in MYCIN derivatives: EMYCIN and NEOMYCIN

It is well known that the problems associated with understanding monitoring and correcting the behavior of an expert system multiply as the knowledge base increases .

For example , it becomes more difficult to ensure that “new” rules are consistent with “old” ones, and to understand the flow of control in situations where large numbers of applicable rules may be in competition for the attention of the interpreter.

MYCIN developed and elaborate MYCIN’s facilities to some extent . Thus EXPLAIN , TEST and REVIEW commands were provided as debugging aids for knowledge engineer . As in MYCIN , EXPLAIN worked by printing each rule that contributed to the conclusion, together with :

16.1.2 EXPLANATION in MYCIN derivatives: EMYCIN and NEOMYCIN (cont.)

As in MYCIN , EXPLAIN worked by printing each rule that contributed to the conclusion, together with :

1. The certainty factor .

2. The “tally” value .

3. The last question asked by the system .

The use of meta-rules in MYCIN and EMYCIN , which was intended to :

1. Make some of the control choices explicit and

2. Open the door to reasoning about problem solving strategy .

16.1.2 EXPLANATION in MYCIN derivatives: EMYCIN and NEOMYCIN (cont.)

Two rational reconstructions of the early Stanford work were begun at the end of the 1970’s . One was the NEOMYCIN system . Which represented an attempt to take a more abstract approach to MYCIN style medical problem solving , based on epistemological and physical consideration .

Thus NEOMYCIN was much more concerned with the simulation of human problem solving than MYCIMN .

NEOMYCIN had the following basic organization :

1. Strategic knowledge was separate out from the medical knowledge and encoded in meta-rules.

2. Diseases were organized taxonomically .

16.1.2 EXPLANATION in MYCIN derivatives: EMYCIN and NEOMYCIN (cont.)

Note : both of the above kinds of knowledge were kept separate from the rules .

(The basic approach is still based on HURISTIC classification

but representation structure and controls use domain rules . )

The domain rules are differentiated into 4 classes :

1. Casual rules .

2. Trigger rules .

3. Data rules .

4. Screening rule .

16.1.2 EXPLANATION in MYCIN derivatives: EMYCIN and NEOMYCIN (cont.)

Thus , in addition we elicit particular data from the user , there is a NEOMYCIN meta-rule which guides the asking questions .

Such rules can then be cited as an explanation of why a particular question was asked .